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Comparison of nice classification for optical diagnosis of colorectal polyps and morphology of removed lesions depending on localisation in colon

Authors :
Vilkoite, Ilona
Mežmale, Linda
Tolmanis, Ivars
Meri, Hosams Abu
Veide, Laura
Dzērve, Zane
Anarkulova, Linda
Nevidovska, Kristīne
Lejnieks, Aivars
Source :
Proceedings of the Latvia University of Agriculture; December 2022, Vol. 76 Issue: 5-6 p650-656, 7p
Publication Year :
2022

Abstract

The narrow-band imaging (NBI) International Colorectal Endoscopic (NICE) classification is based on narrow-band pictures of colon polyps viewed through a narrow-band spectrum. The categorisation utilises staining, surface structure, and vascular patterns to differentiate between hyperplastic and adenomatous colon polyps. It is known that accuracy of the NICE classification for colorectal polyps varies depending on the localisation in the colon.The aim of this study was to compare the diagnostic accuracy of the NICE classification and the gold standard — morphological analysis for the determination of the type of colorectal lesions depending on localisation in colon. A prospective study was performed in an outpatient clinic. 1214 colonoscopies were performed by two expert endoscopists and 475 polyps were found in 291 patients. The overall diagnostic accuracy of the NICE classification was 80.3%. Optical verification was better in ascending colon — 93.9%, followed by sigmoid colon — 82.1%. Inferior results were found for the descending colon — 64.0%. The results of this study showed that the NICE classification could be a helpful instrument in daily practice for the ascending and sigmoid colon. For better results, proper training should be considered. The NICE system could have a role in the replacement of morphological analysis if appropriate results of verification could be achieved.

Details

Language :
English
ISSN :
14074427
Volume :
76
Issue :
5-6
Database :
Supplemental Index
Journal :
Proceedings of the Latvia University of Agriculture
Publication Type :
Periodical
Accession number :
ejs61378919
Full Text :
https://doi.org/10.2478/prolas-2022-0100